Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Arielkanevsky/Complaints_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Arielkanevsky/Complaints_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Arielkanevsky/Complaints_Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Arielkanevsky/Complaints_Classifier") model = AutoModelForSequenceClassification.from_pretrained("Arielkanevsky/Complaints_Classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e49b1c1ee43b081e06cac82e4717fe7557cc56893e192955d3ec5c2e3d2709a7
- Size of remote file:
- 268 MB
- SHA256:
- e8a4f286b8fb385b78b1fc1106324c141aad8fe8e82c4ed468949344b082e9cf
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